CN109586645A - A kind of permanent magnet synchronous motor inertia recognition methods and equipment - Google Patents
A kind of permanent magnet synchronous motor inertia recognition methods and equipment Download PDFInfo
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- CN109586645A CN109586645A CN201811439634.1A CN201811439634A CN109586645A CN 109586645 A CN109586645 A CN 109586645A CN 201811439634 A CN201811439634 A CN 201811439634A CN 109586645 A CN109586645 A CN 109586645A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P23/00—Arrangements or methods for the control of AC motors characterised by a control method other than vector control
- H02P23/14—Estimation or adaptation of motor parameters, e.g. rotor time constant, flux, speed, current or voltage
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
- H02P21/14—Estimation or adaptation of machine parameters, e.g. flux, current or voltage
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P25/00—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details
- H02P25/02—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details characterised by the kind of motor
- H02P25/022—Synchronous motors
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P2207/00—Indexing scheme relating to controlling arrangements characterised by the type of motor
- H02P2207/05—Synchronous machines, e.g. with permanent magnets or DC excitation
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- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Control Of Ac Motors In General (AREA)
- Control Of Electric Motors In General (AREA)
Abstract
The invention discloses a kind of permanent magnet synchronous motor inertia recognition methods and equipment, first obtain the d-q shaft current and revolving speed of the rotor of permanent magnet synchronous motor, the result of previous estimation is modified using the observation data newly introduced according to recursive algorithm using least square method again, obtain new estimates of parameters, wherein forgetting factor λ is updated according to following methods: taking the accumulation E (k) of the Identification Errors in N number of sampling period as judge index, lesser forgetting factor is chosen when E (k) is larger, and biggish forgetting factor is chosen when E (k) is smaller, last basisCalculate rotary inertia.The present invention can also obtain high-precision identification result when rotary inertia changes.
Description
Technical field
The present invention relates to permanent magnet synchronous motor fields, identify aspect more specifically to permanent magnet synchronous motor inertia, especially
It is to be related to a kind of recognition methods of permanent magnet synchronous motor inertia and equipment based on change forgetting factor least square method of recursion.
Background technique
Permanent magnet synchronous motor (PMSM) servo-system is widely used in high-performance, high-precision control occasion, however PMSM
System there are problems that electrically and mechanically working in coordination in practice in engineering, can be right when the variation of the load rotating inertia of motor
System servo characteristic causes significantly to influence.Therefore, the control parameter of high performance servo system should with the variation of load inertia and
Constantly adjustment, to guarantee the stabilization of system performance.The top priority for realizing this control strategy is necessary real-time identification load
Then rotary inertia could adjust control loop parameter according to identified parameters, guarantee the robustness of servo-system.
Least squares identification principle is simple, it is easy to accomplish, there is good statistical property.In servo-system rotary inertia
Identification aspect is applied.Forgetting factor is introduced in least square method, can to time-varying parameter realize on-line identification, but this
The difficult point of kind identification algorithm is the determination of forgetting factor, and forgetting factor is too small, and parameter Estimation fluctuation is too big；Forgetting factor is too
Greatly, then the ability for tracking time-varying parameter will be very weak.Existing method is to choose forgetting factor to obtain identification precision and parameter
The compromise of tracking ability, it is difficult to guarantee to obtain preferable effect at two aspects.
Existing similar published patent:
The Harbin rotary inertia on-line identification method (CN103219939A) work of permanent magnet synchronous motor (PMSM) AC servo system
Sparetime university is learned
The step of patent, is:
Step 1: constant load perturbing torque value TL is picked out using Load Torque Identification portion；
Whether step 2: being in that dynamic change rank is disconnected to be judged using system dynamical state judging part to motor speed,
When motor speed is in the dynamic change stage, and the change rate of motor speed is higher than motor identification of rotational inertia threshold variations rate
When, it is calculated using the least squares estimate based on recursion and obtains rotary inertia estimated value；
Step 3: judge whether the rotary inertia on-line identification process meets the output rotary inertia estimated value pre-seted
Condition, if so, output rotary inertia estimated value, executes step 4, otherwise return step two；
Step 4: judging whether the rotary inertia estimated value of output meets required precision, if so, rotary inertia on-line identification
Process terminates；Otherwise, return step two.
Prior art Shortcomings:
Obviously, existing method has no idea to accurately track its variation when rotary inertia changes.
The most significant feature of least square method of recursion is exactly that will appear data saturated phenomenon.When data volume reaches a certain amount of
Later, the variation that this method treats identified parameters can become insensitive.Although this method utilizes the available essence of least square method
Spend high as a result, can not still be applied to the occasion of rotary inertia time-varying, the application range of on-line identification is limited.
Summary of the invention
The technical problem to be solved in the present invention is that for the most significant feature of least square method of recursion in the prior art
Exactly will appear data saturated phenomenon, when data volume reaches it is a certain amount of after, the variation that this method treats identified parameters can become
It is insensitive, although this method is high using the available precision of least square method as a result, can not be applied to rotary inertia
The occasion of time-varying, the limited technological deficiency of the application range of on-line identification provide a kind of based on change forgetting factor recursion minimum two
The permanent magnet synchronous motor inertia recognition methods of multiplication.
Therefore, the invention patent for this problem, on the basis of traditional least square method, passes through the variable something lost of addition
Forget the factor, at identification initial stage, accelerate the tracking effect of identification algorithm by choosing lesser forgetting factor, in the switching of identification later period
Biggish forgetting factor promotes identification precision, and then when rotary inertia changes, can also obtain high-precision identification
As a result.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples, in attached drawing:
Fig. 1 is permanent magnet synchronous motor mechanical equation discretization schematic diagram；
Fig. 2 is the flow chart of one embodiment of permanent magnet synchronous motor inertia recognition methods；
Fig. 3 is the flow chart that forgetting factor selects a regular embodiment.
Specific embodiment
For a clearer understanding of the technical characteristics, objects and effects of the present invention, now control attached drawing is described in detail
A specific embodiment of the invention.
It is following that first the principle of the present invention is introduced.
Permanent magnet synchronous motor mechanical equation includes rotary inertia, as shown in following formula one:
In formula: J --- rotary inertia；
Te--- electromagnetic torque；Tl--- load torque；B --- viscous friction coefficient；W --- rotor velocity.
Enable y (s)=w (s), u (s)=Te(s)-Tl(s),Discretization modeling is carried out to it, and
Zero-order holder is added, the discretized system such as Fig. 1 can be obtained
It can obtain:Therefore, the discrete side of machinery of the permanent magnet synchronous motor of available discretization
Journey is following such as formula two:
Least square method of recursion is to work as to be identified system at runtime, after every primary new observation data of acquirement, just preceding
On the basis of secondary estimated result, the result of previous estimation is modified using the observation data newly introduced according to recursive algorithm,
It obtains new estimates of parameters, reduces evaluated error.In this way, with the gradually introducing of new observation data, once connect once into
Row parameter Estimation, until estimates of parameters reaches satisfied levels of precision.Traditional following formula of least square method recursive algorithm
(3) as follows:
In formula:--- the estimated value of parameter θ to be identified；L (k) --- gain vector；P (k) --- covariance matrix；--- information vector, K (k) they are kalman gain matrix, and k indicates timing, and y (k)=w (k), T are transposition, L (K), P (k)
It is median, needs initially to give, can changes with the identification process of least square method recursive algorithm, be that those skilled in the art are normal
Know.
With the increase of processing data, " data saturation " phenomenon will occur in least square method of recursion, i.e. new data generates
Identification result will receive the influence of historical data and become inaccuracy, cause the algorithm identification later period to occur insensitive to Parameters variation
The case where, thus can not effectively tracking parameter variation.For the generation for preventing this phenomenon, introduced on the basis of least square method
Forgetting factor, to performance indicator makes certain amendment.
If objective functionSo in formula, γ is forgetting factor, 0
< γ≤1, L are that current timing.According to above formula, compare the formula of traditional least square method of recursion, can band forget because
For example following formula four of the iterative algorithm of sub- least square method of recursion parameter estimation:
The selection of forgetting factor can generate large effect to the performance of algorithm, and when forgetting factor is larger, identification precision is high,
Convergence rate is slow, insensitive to the variation of parameter；And forgetting factor it is smaller when, fast convergence rate is sensitive to Parameters variation, simultaneously
Identification precision can reduce.
The mechanical equation of the permanent magnet synchronous motor of discretization shown in reference formula two carries out used based on least square method rotation
Measure discrimination method design.It enables1=nTl(k-1), it according to formula four, can obtain:θ=[n, m, l]T,
According to above-mentioned principle, the solution of the present invention is as follows:
With reference to Fig. 2, a kind of permanent magnet synchronous motor inertia based on change forgetting factor least square method of recursion of the present embodiment
Recognition methods comprises the following steps:
S1, obtain permanent magnet synchronous motor rotor d-q shaft current and revolving speed；
S2, it is carried out according to recursive algorithm using result of the observation data newly introduced to previous estimation using least square method
Amendment, show that new estimates of parameters, the formula of recursive algorithm are as follows:
In formula, forgetting factor λ is updated according to following methods: taking the accumulation E of the Identification Errors e (k) in N number of sampling period
(k) be used as judge index, lesser forgetting factor is chosen when E (k) is larger, and chosen when E (k) is smaller biggish forgetting because
Son, 0 γ≤1 <；
S3, basisCalculate rotary inertia J；Specific computation rule can be according to formula It obtains；
Wherein, k indicates timing,Indicate the estimated value of parameter θ to be identified, θ=[n, m, l]T, P (k) expression covariance
Matrix, L (k) indicate gain vector,Y (k)=w (k), T indicate to turn
It sets,L=nTl(k-1), E (k)=+ e (k- (N-1))+...+e (k-1)+e (k), N is big
In 1 positive integer, Te、Tl, b, w respectively indicate permanent magnet synchronous motor electromagnetic torque, load
Torque, viscous friction coefficient, rotor velocity.TeIt is calculated according to following formula: Te=Kt[ψiq+(Ld-Lq)idiq], wherein
KtIt is constant, LdIt is motor in the inductance of d axis and q axis with Lq and is priori value, idAnd iqRespectively electricity of the motor in d axis and q axis
Stream.
With reference to Fig. 3, the specific update method of forgetting factor λ are as follows:
According to calculating E (k)；
Judge E (k) and two threshold value m1And m2Size relation, m1> m2If E (k) is less than m2, then λ is updated to a, if
m2≤ E (k) < m1, then λ is updated to b, if E (k) >=m2, then λ is updated to c；Wherein a, b, c are preset value, a > b > c.
It is corresponding with the above method, it is of the invention based on the permanent magnet synchronous motor inertia for becoming forgetting factor least square method of recursion
Identification device includes:
Computer storage medium includes:
(1) for obtaining the d-q shaft current of the rotor of permanent magnet synchronous motor and the software code of revolving speed；
(2) for utilizing the observation data newly introduced to the result of previous estimation according to recursive algorithm using least square method
It is modified, show that the software code of new estimates of parameters, the formula of recursive algorithm are as follows:
In formula, forgetting factor λ is updated according to following methods: taking the accumulation E of the Identification Errors e (k) in N number of sampling period
(k) be used as judge index, lesser forgetting factor is chosen when E (k) is larger, and chosen when E (k) is smaller biggish forgetting because
Son, 0 γ≤1 <；
(3) it is used for basisCalculate the software code of rotary inertia；
Wherein, k indicates timing,Indicate the estimated value of parameter θ to be identified, θ=[n, m, l]T, P (k) expression covariance
Matrix, L (k) indicate gain vector,Y (k)=w (k), T indicate to turn
It sets,L=nTl(k-1), E (k)=+ e (k- (N-1))+...+e (k-1)+e (k), N is big
In 1 positive integer, Te、Tl, b, w respectively indicate permanent magnet synchronous motor electromagnetic torque, load
Torque, viscous friction coefficient, rotor velocity.TeIt is calculated according to following formula: Te=Kt[ψiq+(Ld-Lq)idiq], wherein
KtIt is constant, LdIt is motor in the inductance of d axis and q axis with Lq and is priori value, idAnd iqRespectively electricity of the motor in d axis and q axis
Stream.
The specific update method of forgetting factor λ are as follows:
According to calculating E (k)；
Judge E (k) and two threshold value m1And m2Size relation, m1> m2If E (k) is less than m2, then λ is updated to a, if
m2≤ E (k) < m1, then λ is updated to b, if E (k) >=m2, then λ is updated to c；Wherein a, b, c are preset value, a > b > c.
The embodiment of the present invention is described with above attached drawing, but the invention is not limited to above-mentioned specific
Embodiment, the above mentioned embodiment is only schematical, rather than restrictive, those skilled in the art
Under the inspiration of the present invention, without breaking away from the scope protected by the purposes and claims of the present invention, it can also make very much
Form, all of these belong to the protection of the present invention.
Claims (6)
1. a kind of based on the permanent magnet synchronous motor inertia recognition methods for becoming forgetting factor least square method of recursion, which is characterized in that
It comprises the following steps:
S1, obtain permanent magnet synchronous motor rotor d-q shaft current and revolving speed；
S2, the result of previous estimation is repaired using the observation data newly introduced according to recursive algorithm using least square method
Just, show that new estimates of parameters, the formula of recursive algorithm are as follows:
In formula, forgetting factor λ is updated according to following methods: taking the accumulation E (k) of the Identification Errors e (k) in N number of sampling period
As judge index, lesser forgetting factor is chosen when E (k) is larger, and biggish forgetting factor is chosen when E (k) is smaller,
0 γ≤1 <；
S3, basisCalculate rotary inertia；
Wherein, k indicates timing,Indicate the estimated value of parameter θ to be identified, θ=[n, m, l]T, P (k) expression covariance square
Battle array, L (k) indicate gain vector,Y (k)=w (k), T indicate to turn
It sets,L=nTl(k-1), E (k)=e (k-N)+e (k- (N-1))+...+e (k-1)+e (k),
N is the positive integer greater than 1,Te、Tl, b, w respectively indicate permanent magnet synchronous motor electromagnetism turn
Square, load torque, viscous friction coefficient, rotor velocity.
2. permanent magnet synchronous motor inertia recognition methods according to claim 1, which is characterized in that forgetting factor λ's is specific
Update method are as follows:
According to calculating E (k)；
Judge E (k) and two threshold value m1And m2Size relation, m1> m2If E (k) is less than m2, then λ is updated to a, if m2≤E
(k) < m1, then λ is updated to b, if E (k) >=m2, then λ is updated to c；Wherein a, b, c are preset value, a > b > c.
3. permanent magnet synchronous motor inertia recognition methods according to claim 1, which is characterized in that TeAccording to following formula meters
It obtains: Te=Kt[iq+(Ld-Lq)idiq], wherein KtIt is constant, LdIt is motor in the inductance of d axis and q axis with Lq and is priori
Value, idAnd iqRespectively electric current of the motor in d axis and q axis.
4. a kind of identify equipment based on the permanent magnet synchronous motor inertia for becoming forgetting factor least square method of recursion, which is characterized in that
Include:
Computer storage medium includes:
(1) for obtaining the d-q shaft current of the rotor of permanent magnet synchronous motor and the software code of revolving speed；
(2) for being carried out according to recursive algorithm using result of the observation data newly introduced to previous estimation using least square method
Amendment, show that the software code of new estimates of parameters, the formula of recursive algorithm are as follows:
In formula, forgetting factor λ is updated according to following methods: taking the accumulation E (k) of the Identification Errors e (k) in N number of sampling period
As judge index, lesser forgetting factor is chosen when E (k) is larger, and biggish forgetting factor is chosen when E (k) is smaller,
0 γ≤1 <；
(3) it is used for basisCalculate the software code of rotary inertia；
Wherein, k indicates timing,Indicate the estimated value of parameter θ to be identified, θ=[n, m, l]T, P (k) expression covariance square
Battle array, L (k) indicate gain vector,Y (k)=w (k), T indicate to turn
It sets,L=nTl(k-1), E (k)=e (k-N)+e (k- (N-1))+...+e (k-1)+e (k),
N is the positive integer greater than 1,Te、Tl, b, w respectively indicate permanent magnet synchronous motor electromagnetism turn
Square, load torque, viscous friction coefficient, rotor velocity.
5. permanent magnet synchronous motor inertia according to claim 4 identifies equipment, which is characterized in that forgetting factor λ's is specific
Update method are as follows:
According to calculating E (k)；
Judge E (k) and two threshold value m1And m2Size relation, m1> m2If E (k) is less than m2, then λ is updated to a, if m2≤E
(k) < m1, then λ is updated to b, if E (k) >=m2, then λ is updated to c；Wherein a, b, c are preset value, a > b > c.
6. permanent magnet synchronous motor inertia according to claim 4 identifies equipment, which is characterized in that TeAccording to following formula meters
It obtains: Te=Kt[iq+(Ld-Lq)idiq], wherein KtIt is constant, LdIt is motor in the inductance of d axis and q axis with Lq and is priori
Value, idAnd iqRespectively electric current of the motor in d axis and q axis.
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Cited By (5)
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| CN110861497A (en) * | 2019-11-28 | 2020-03-06 | 安徽江淮汽车集团股份有限公司 | Electric vehicle shake detection method and device, electronic equipment and storage medium |
| CN112415392A (en) * | 2020-11-03 | 2021-02-26 | 珠海格力电器股份有限公司 | Method for determining forgetting factor, electronic equipment, storage medium and device |
| CN112960501A (en) * | 2021-02-23 | 2021-06-15 | 杭州优迈科技有限公司 | Elevator operation control method and device and electronic equipment |
| CN113965131A (en) * | 2020-07-20 | 2022-01-21 | 广东博智林机器人有限公司 | Rotational inertia identification method and device |
| CN114337427A (en) * | 2021-12-17 | 2022-04-12 | 南京理工大学 | Rotational inertia identification method of recursive least square method with forgetting factor |
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Cited By (6)
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| CN114337427A (en) * | 2021-12-17 | 2022-04-12 | 南京理工大学 | Rotational inertia identification method of recursive least square method with forgetting factor |
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